Open Access
Subscription Access
Factors Influencing the Use of Internet of Things (IOT) in Grocery Shopping in Pune
With self-driving cars, virtual assistants and smart carts helping consumers buy products, to fully automated hotels having few or no staff present in them, the world is spurting up with the Internet of things (IOT) technology in full swing. This paper attempted to detect the factors influencing the use of IOT in consumers buying grocery in Pune. The study was conducted as compared to five factors influencing the usage of IOT while shopping that is engagement, availability of variety, self-service, real time data availability and product quality information. Data was collected from 260 respondents residing in Pune by means of an online survey. The research shows that amongst the five factors “engagement” was the highest valued factor with a variance of 19.176%, followed by product quality information, self-service, real time data availability and availability of variety all in decreasing order of variance. The findings of this study aim to contribute the vital stats to the companies who are working on researching, designing and preparing product which are a constituent of IOT and retailers who are planning to enhance their customer and market reach strategy.
Keywords
Internet of Things (IOT), Engagement, Availability of Variety, Self-Service, Real Time Data Availability, Product Quality Information.
User
Font Size
Information
- Abbasy M. &. (2017). Predictable Influence of IoT (Internet of Things) in the Higher Education. . International Journal of Information and Education Technology, 7,, 914- 920.
- Abbasy M. B. & Quesada E. V. (2017). Predictable Influence of IoT (Internet of Things) in the Higher Education. International Journal of Information and Education Technology,7(12), , 914-920. doi: doi:10.18178/ijiet.2017.7.12.995
- Amara, L. A. (2011). ECloudRFID – A mobile software framework architecture for pervasive RFID-based applications. Journal of Network and Computer Applications, 34(3),, 972-979.
- Ashton K. (2009). That ‘internet of things’ thing. RFID journal 22 (7), 97-114.
- Atzori L. I. (2010). The Internet of thing : A Survey. Computer Networks, 54, (15), 2787-2805.
- Balaji M. a. (2016). Value co-creation with Internet of things technology in the retail industry. Journal of Marketing Management, 33(1-2), 7-31.
- Bouzembrak Y. K. & Marvin H. J. (2019). Internet of Things in food safety: Literature review and a bibliometric analysis. Trends in Food Science & Technology, 94, , 54-64.
- Bowden J. (2009). The process of customer engagement: A conceptual framework. . Journal of Marketing Theory and Practice, 17(1), 63-74.
- Brynjolfsson E. H. (2013). Competing in the Age of Omnichannel Retailing. MIT Sloan Management Review, 54(4),, 23–29.
- Calder B. J. (2009). An Experimental Study of the Relationship between Online Engagement and Advertising Effectiveness. Journal of Interactive Marketing, 23(4), 321-331.
- Calder B. M. (2009). An Experimental Study of the Relationship between Online Engagement and Advertising Effectiveness. Journal of Interactive Marketing 23 (4), 321–331.
- Dulabh M. C. (2017). Measuring Consumer Engagement in the Brain to Online Interactive Shopping Environments. In &. M. T. Jung, Augmented Reality and Virtual Reality- Empowering Human, Place and Business. (1 ed.) (pp. 145-168). Springer Nature.
- Fagerstrøm A. E. & Sigurdsson V. (2020). Investigating the impact of Internet of Things services from a smartphone app on grocery shopping. Journal of Retailing and Consumer Services, 52,. doi: 101927.doi:10.1016/j.jretconser.2019.101927
- Gregory J. (2015). The Internet of Things: Revolutionizing the Retail Industry. Accenture.
- Gubbi J. B. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. . Future Generation Computer Systems, 29,, 1645--1660.
- Guo X. L., & Liu M. (2012). Evaluating Factors Influencing Consumer Satisfaction towards Online Shopping in China. . Asian Social Science, 8(13). doi:doi:10.5539/ass.v8n13p40
- Hair Jr J. F. (2010). Multivariate data analysis (7th ed.). . United States of America,: Pearson.
- Hollebeek L. D. (2014). Consumer Brand Engagement in Social Media: Conceptualization, Scale Development and Validation. Journal of Interactive Marketing 28 (2), 149–165.
- Miorandi D. S. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10, (7),, 1497-1516.
- Mollen A. a. (2010). Engagement, Telepresence and Interactivity in Online Consumer Experience: Reconciling Scholastic and Managerial Perspectives. . Journal of Business Research, 63, , 919-925.
- Mosquera A. P. (2017). Understanding the customer experience in the age of omnichannel shopping. Icono 14, volumen 15 (2), 235-255.
- Özdemir V. &. (2018 ). Birth of Industry 5.0: Making Sense of Big Data with Artificial Intelligence,. "The Internet of Things" and Next-Generation Technology Policy Omics : a journal of integrative biology, 22(1), 65–76.
- Payne J. S. (2013). Gendering the machine: preferred virtual assistant gender and realism in self-service. In B. K. R. Aylett (Ed.), Intelligent Virtual Agents: 13th International Conference (pp. 106-115). Edinburgh, UK: Springer-Verlag.
- Sharma P. S. (2010). Exploring impulse buying and variety seeking by retail shoppers: towards a common conceptual framework. . Journal of Marketing Management. 26 (5- 6), 473-494.
- Thakur R. (2016). Understanding Customer Engagement and Loyalty: A Case of Mobile Devices for Shopping. . Journal of Retailing and Consumer Services, 32,, 151- 163.
- Verma S. K. (2017). A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues. . IEEE Communications Surveys & Tutorials, 19, 1457-1477.
- Zhang J. W. (2009). The effectiveness of customized promotions in online and offline stores. J. Mark. Res. 46 (2),, 190–206.
Abstract Views: 142
PDF Views: 91